submission_id: mistralai-mixtral-8x7b-instruct-v0-1_v3
developer_uid: robert_irvine
status: torndown
model_repo: mistralai/Mixtral-8x7B-Instruct-v0.1
reward_repo: rirv938/reward_gpt2_medium_preference_24m_e2
generation_params: {'temperature': 1.0, 'top_p': 1.0, 'min_p': 0.0, 'top_k': 50, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['</s>', '<|user|>', '###', '\n'], 'max_input_tokens': 512, 'best_of': 4, 'max_output_tokens': 64}
formatter: {'memory_template': '<s>[INST] This is an entertaining conversation. You are {bot_name} who has the persona: {memory}.\nPlay the role of {bot_name}. Engage in a chat with {user_name} while staying in character. You should create a fun dialogue which entertains {user_name}. \n', 'prompt_template': '{prompt}\n', 'bot_template': '{bot_name}: {message}</s>', 'user_template': '[INST]{user_name}: {message}[/INST]', 'response_template': '{bot_name}:', 'truncate_by_message': False}
reward_formatter: {'memory_template': 'Memory: {memory}\n', 'prompt_template': '{prompt}\n', 'bot_template': 'Bot: {message}\n', 'user_template': 'User: {message}\n', 'response_template': 'Bot:', 'truncate_by_message': False}
timestamp: 2024-03-17T22:15:09+00:00
model_name: mistralai-mixtral-8x7b-instruct-v0-1_v3
model_eval_status: pending
model_group: mistralai/Mixtral-8x7B-I
num_battles: 1360153
num_wins: 720906
celo_rating: 1173.46
propriety_score: 0.0
propriety_total_count: 0.0
submission_type: basic
model_architecture: None
model_num_parameters: 46702792704.0
best_of: 4
max_input_tokens: 512
max_output_tokens: 64
display_name: mistralai-mixtral-8x7b-instruct-v0-1_v3
ineligible_reason: propriety_total_count < 800
language_model: mistralai/Mixtral-8x7B-Instruct-v0.1
model_size: 47B
reward_model: rirv938/reward_gpt2_medium_preference_24m_e2
us_pacific_date: 2024-03-17
win_ratio: 0.5300183141161325
preference_data_url: None
Resubmit model
Running pipeline stage MKMLizer
Starting job with name mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer
Waiting for job on mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer to finish
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: ║     _____            __           __                                ║
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: ║       /___/                                                         ║
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: ║                                                                     ║
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: ║  Version: 0.8.6                                                     ║
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: ║                                                                     ║
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: ║  The license key for the current software has been verified as      ║
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: ║  belonging to:                                                      ║
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: ║                                                                     ║
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: ║  Chai Research Corp.                                                ║
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: ║  Expiration: 2024-04-15 23:59:59                                    ║
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: ║                                                                     ║
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: /opt/conda/lib/python3.10/site-packages/huggingface_hub/utils/_deprecation.py:131: FutureWarning: 'list_files_info' (from 'huggingface_hub.hf_api') is deprecated and will be removed from version '0.23'. Use `list_repo_tree` and `get_paths_info` instead.
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer:   warnings.warn(warning_message, FutureWarning)
Retrying (%r) after connection broken by '%r': %s
Retrying (%r) after connection broken by '%r': %s
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: Downloaded to shared memory in 71.064s
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: quantizing model to /dev/shm/model_cache
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: Saving flywheel model at /dev/shm/model_cache
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: quantized model in 57.798s
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: Processed model mistralai/Mixtral-8x7B-Instruct-v0.1 in 134.496s
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: creating bucket guanaco-mkml-models
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/mistralai-mixtral-8x7b-instruct-v0-1-v3
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/mistralai-mixtral-8x7b-instruct-v0-1-v3/special_tokens_map.json
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/mistralai-mixtral-8x7b-instruct-v0-1-v3/tokenizer_config.json
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/mistralai-mixtral-8x7b-instruct-v0-1-v3/tokenizer.json
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer.model s3://guanaco-mkml-models/mistralai-mixtral-8x7b-instruct-v0-1-v3/tokenizer.model
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/mistralai-mixtral-8x7b-instruct-v0-1-v3/config.json
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: cp /dev/shm/model_cache/flywheel_model.3.safetensors s3://guanaco-mkml-models/mistralai-mixtral-8x7b-instruct-v0-1-v3/flywheel_model.3.safetensors
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/mistralai-mixtral-8x7b-instruct-v0-1-v3/flywheel_model.0.safetensors
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: cp /dev/shm/model_cache/flywheel_model.2.safetensors s3://guanaco-mkml-models/mistralai-mixtral-8x7b-instruct-v0-1-v3/flywheel_model.2.safetensors
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: cp /dev/shm/model_cache/flywheel_model.1.safetensors s3://guanaco-mkml-models/mistralai-mixtral-8x7b-instruct-v0-1-v3/flywheel_model.1.safetensors
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: loading reward model from rirv938/reward_gpt2_medium_preference_24m_e2
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: 
Loading 0:   0%|          | 0/995 [00:00<?, ?it/s]
Loading 0:   1%|          | 7/995 [00:00<00:14, 69.45it/s]
Loading 0:   1%|▏         | 14/995 [00:00<00:15, 64.32it/s]
Loading 0:   2%|▏         | 21/995 [00:00<00:15, 61.48it/s]
Loading 0:   3%|▎         | 34/995 [00:00<00:11, 82.50it/s]
Loading 0:   4%|▍         | 43/995 [00:00<00:13, 72.59it/s]
Loading 0:   5%|▌         | 52/995 [00:00<00:20, 45.39it/s]
Loading 0:   6%|▌         | 59/995 [00:01<00:19, 48.67it/s]
Loading 0:   7%|▋         | 68/995 [00:01<00:16, 55.83it/s]
Loading 0:   8%|▊         | 75/995 [00:01<00:15, 57.97it/s]
Loading 0:   8%|▊         | 82/995 [00:01<00:15, 58.72it/s]
Loading 0:  10%|▉         | 95/995 [00:01<00:12, 74.63it/s]
Loading 0:  10%|█         | 104/995 [00:01<00:11, 77.39it/s]
Loading 0:  11%|█▏        | 113/995 [00:02<00:19, 44.58it/s]
Loading 0:  12%|█▏        | 120/995 [00:02<00:18, 47.68it/s]
Loading 0:  13%|█▎        | 128/995 [00:02<00:16, 53.96it/s]
Loading 0:  14%|█▎        | 135/995 [00:02<00:15, 55.75it/s]
Loading 0:  14%|█▍        | 142/995 [00:02<00:14, 57.13it/s]
Loading 0:  15%|█▍        | 149/995 [00:02<00:14, 58.20it/s]
Loading 0:  16%|█▋        | 162/995 [00:02<00:16, 49.20it/s]
Loading 0:  17%|█▋        | 168/995 [00:02<00:16, 51.20it/s]
Loading 0:  18%|█▊        | 175/995 [00:03<00:15, 53.35it/s]
Loading 0:  18%|█▊        | 182/995 [00:03<00:14, 55.41it/s]
Loading 0:  19%|█▉        | 191/995 [00:03<00:13, 61.73it/s]
Loading 0:  20%|█▉        | 198/995 [00:03<00:12, 61.70it/s]
Loading 0:  21%|██        | 205/995 [00:03<00:12, 63.69it/s]
Loading 0:  21%|██▏       | 212/995 [00:03<00:19, 39.94it/s]
Loading 0:  22%|██▏       | 221/995 [00:04<00:16, 48.05it/s]
Loading 0:  23%|██▎       | 228/995 [00:04<00:14, 51.22it/s]
Loading 0:  24%|██▎       | 235/995 [00:04<00:14, 53.71it/s]
Loading 0:  24%|██▍       | 242/995 [00:04<00:13, 55.42it/s]
Loading 0:  26%|██▌       | 255/995 [00:04<00:10, 72.07it/s]
Loading 0:  27%|██▋       | 265/995 [00:04<00:15, 47.95it/s]
Loading 0:  28%|██▊       | 276/995 [00:04<00:12, 58.03it/s]
Loading 0:  29%|██▊       | 284/995 [00:15<04:11,  2.83it/s]
Loading 0:  29%|██▉       | 293/995 [00:15<02:58,  3.94it/s]
Loading 0:  30%|███       | 301/995 [00:15<02:11,  5.28it/s]
Loading 0:  31%|███       | 309/995 [00:15<01:36,  7.10it/s]
Loading 0:  32%|███▏      | 320/995 [00:16<01:13,  9.18it/s]
Loading 0:  33%|███▎      | 327/995 [00:16<00:57, 11.59it/s]
Loading 0:  34%|███▎      | 334/995 [00:16<00:45, 14.68it/s]
Loading 0:  34%|███▍      | 343/995 [00:16<00:32, 19.97it/s]
Loading 0:  35%|███▌      | 350/995 [00:16<00:26, 24.37it/s]
Loading 0:  36%|███▌      | 357/995 [00:16<00:21, 29.22it/s]
Loading 0:  37%|███▋      | 368/995 [00:17<00:21, 29.27it/s]
Loading 0:  38%|███▊      | 377/995 [00:17<00:16, 36.37it/s]
Loading 0:  39%|███▊      | 384/995 [00:17<00:14, 40.76it/s]
Loading 0:  39%|███▉      | 391/995 [00:17<00:13, 44.93it/s]
Loading 0:  40%|████      | 402/995 [00:17<00:10, 57.50it/s]
Loading 0:  41%|████▏     | 411/995 [00:17<00:09, 62.55it/s]
Loading 0:  42%|████▏     | 420/995 [00:17<00:08, 68.57it/s]
Loading 0:  43%|████▎     | 429/995 [00:18<00:12, 43.61it/s]
Loading 0:  44%|████▍     | 438/995 [00:18<00:10, 50.64it/s]
Loading 0:  45%|████▍     | 445/995 [00:18<00:10, 53.35it/s]
Loading 0:  45%|████▌     | 452/995 [00:18<00:09, 55.24it/s]
Loading 0:  46%|████▌     | 459/995 [00:18<00:09, 56.24it/s]
Loading 0:  47%|████▋     | 472/995 [00:18<00:07, 71.64it/s]
Loading 0:  48%|████▊     | 480/995 [00:19<00:10, 47.91it/s]
Loading 0:  49%|████▉     | 487/995 [00:19<00:10, 50.61it/s]
Loading 0:  50%|████▉     | 494/995 [00:19<00:09, 53.04it/s]
Loading 0:  51%|█████     | 503/995 [00:19<00:08, 59.14it/s]
Loading 0:  51%|█████▏    | 510/995 [00:19<00:08, 59.39it/s]
Loading 0:  52%|█████▏    | 517/995 [00:19<00:08, 59.61it/s]
Loading 0:  53%|█████▎    | 526/995 [00:20<00:11, 41.95it/s]
Loading 0:  54%|█████▍    | 535/995 [00:20<00:09, 49.32it/s]
Loading 0:  54%|█████▍    | 542/995 [00:20<00:08, 52.00it/s]
Loading 0:  55%|█████▌    | 549/995 [00:20<00:08, 54.55it/s]
Loading 0:  56%|█████▋    | 560/995 [00:31<00:07, 54.55it/s]
Loading 0:  56%|█████▋    | 561/995 [00:31<02:37,  2.75it/s]
Loading 0:  57%|█████▋    | 568/995 [00:31<01:58,  3.62it/s]
Loading 0:  58%|█████▊    | 575/995 [00:31<01:27,  4.81it/s]
Loading 0:  58%|█████▊    | 582/995 [00:31<01:11,  5.77it/s]
Loading 0:  59%|█████▉    | 591/995 [00:31<00:48,  8.37it/s]
Loading 0:  60%|██████    | 598/995 [00:32<00:36, 10.94it/s]
Loading 0:  61%|██████    | 605/995 [00:32<00:27, 14.23it/s]
Loading 0:  62%|██████▏   | 612/995 [00:32<00:20, 18.27it/s]
Loading 0:  63%|██████▎   | 625/995 [00:32<00:12, 28.66it/s]
Loading 0:  64%|██████▍   | 636/995 [00:32<00:12, 28.66it/s]
Loading 0:  65%|██████▍   | 643/995 [00:32<00:10, 32.88it/s]
Loading 0:  65%|██████▌   | 650/995 [00:32<00:09, 37.48it/s]
Loading 0:  66%|██████▌   | 659/995 [00:33<00:07, 45.33it/s]
Loading 0:  67%|██████▋   | 666/995 [00:33<00:06, 49.13it/s]
Loading 0:  68%|██████▊   | 673/995 [00:33<00:06, 52.58it/s]
Loading 0:  69%|██████▉   | 689/995 [00:33<00:04, 76.22it/s]
Loading 0:  70%|███████   | 699/995 [00:33<00:06, 46.87it/s]
Loading 0:  71%|███████   | 707/995 [00:33<00:05, 50.07it/s]
Loading 0:  72%|███████▏  | 716/995 [00:34<00:04, 56.24it/s]
Loading 0:  73%|███████▎  | 724/995 [00:34<00:04, 57.22it/s]
Loading 0:  73%|███████▎  | 731/995 [00:34<00:04, 58.05it/s]
Loading 0:  74%|███████▍  | 739/995 [00:34<00:06, 41.63it/s]
Loading 0:  75%|███████▌  | 748/995 [00:34<00:04, 49.82it/s]
Loading 0:  76%|███████▌  | 755/995 [00:34<00:04, 53.63it/s]
Loading 0:  77%|███████▋  | 763/995 [00:34<00:04, 57.72it/s]
Loading 0:  78%|███████▊  | 777/995 [00:35<00:02, 75.43it/s]
Loading 0:  79%|███████▉  | 786/995 [00:35<00:02, 74.19it/s]
Loading 0:  80%|███████▉  | 795/995 [00:35<00:04, 48.96it/s]
Loading 0:  81%|████████  | 802/995 [00:35<00:03, 52.10it/s]
Loading 0:  82%|████████▏ | 811/995 [00:35<00:03, 59.76it/s]
Loading 0:  82%|████████▏ | 819/995 [00:35<00:02, 62.35it/s]
Loading 0:  83%|████████▎ | 827/995 [00:35<00:02, 64.26it/s]
Loading 0:  85%|████████▍ | 841/995 [00:36<00:01, 80.83it/s]
Loading 0:  85%|████████▌ | 850/995 [00:46<00:49,  2.92it/s]
Loading 0:  86%|████████▌ | 857/995 [00:47<00:36,  3.76it/s]
Loading 0:  87%|████████▋ | 866/995 [00:47<00:24,  5.26it/s]
Loading 0:  88%|████████▊ | 875/995 [00:47<00:16,  7.34it/s]
Loading 0:  89%|████████▊ | 883/995 [00:47<00:11,  9.74it/s]
Loading 0:  90%|████████▉ | 891/995 [00:47<00:08, 12.88it/s]
Loading 0:  90%|█████████ | 899/995 [00:47<00:06, 14.45it/s]
Loading 0:  91%|█████████▏| 908/995 [00:48<00:04, 19.55it/s]
Loading 0:  92%|█████████▏| 916/995 [00:48<00:03, 24.74it/s]
Loading 0:  93%|█████████▎| 924/995 [00:48<00:02, 30.60it/s]
Loading 0:  94%|█████████▍| 938/995 [00:48<00:01, 45.22it/s]
Loading 0:  95%|█████████▌| 947/995 [00:48<00:00, 50.97it/s]
Loading 0:  96%|█████████▌| 956/995 [00:50<00:02, 15.72it/s]
Loading 0:  97%|█████████▋| 966/995 [00:50<00:01, 21.12it/s]
Loading 0:  98%|█████████▊| 973/995 [00:50<00:00, 25.29it/s]
Loading 0:  99%|█████████▊| 981/995 [00:50<00:00, 30.75it/s]
Loading 0: 100%|█████████▉| 992/995 [00:50<00:00, 41.15it/s]
                                                            
/opt/conda/lib/python3.10/site-packages/transformers/models/auto/configuration_auto.py:1096: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer:   warnings.warn(
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: /opt/conda/lib/python3.10/site-packages/transformers/models/auto/tokenization_auto.py:720: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer:   warnings.warn(
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: /opt/conda/lib/python3.10/site-packages/transformers/models/auto/auto_factory.py:466: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer:   warnings.warn(
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: /opt/conda/lib/python3.10/site-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly.  To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer:   return self.fget.__get__(instance, owner)()
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: Saving duration: 0.225s
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: Processed model rirv938/reward_gpt2_medium_preference_24m_e2 in 3.893s
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: creating bucket guanaco-reward-models
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: Bucket 's3://guanaco-reward-models/' created
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/mistralai-mixtral-8x7b-instruct-v0-1-v3_reward
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/mistralai-mixtral-8x7b-instruct-v0-1-v3_reward/config.json
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/mistralai-mixtral-8x7b-instruct-v0-1-v3_reward/tokenizer_config.json
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/mistralai-mixtral-8x7b-instruct-v0-1-v3_reward/merges.txt
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/mistralai-mixtral-8x7b-instruct-v0-1-v3_reward/special_tokens_map.json
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/mistralai-mixtral-8x7b-instruct-v0-1-v3_reward/vocab.json
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/mistralai-mixtral-8x7b-instruct-v0-1-v3_reward/tokenizer.json
mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/mistralai-mixtral-8x7b-instruct-v0-1-v3_reward/reward.tensors
Job mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer completed after 225.07s with status: succeeded
Stopping job with name mistralai-mixtral-8x7b-instruct-v0-1-v3-mkmlizer
Pipeline stage MKMLizer completed in 226.38s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.37s
Running pipeline stage ISVCDeployer
Creating inference service mistralai-mixtral-8x7b-instruct-v0-1-v3
Waiting for inference service mistralai-mixtral-8x7b-instruct-v0-1-v3 to be ready
Inference service mistralai-mixtral-8x7b-instruct-v0-1-v3 ready after 293.8180766105652s
Pipeline stage ISVCDeployer completed in 300.51s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.8489952087402344s
Received healthy response to inference request in 2.123744010925293s
Received healthy response to inference request in 2.140990734100342s
Received healthy response to inference request in 2.364474296569824s
Received healthy response to inference request in 1.7580890655517578s
5 requests
0 failed requests
5th percentile: 1.8312200546264648
10th percentile: 1.904351043701172
20th percentile: 2.050613021850586
30th percentile: 2.1271933555603026
40th percentile: 2.1340920448303224
50th percentile: 2.140990734100342
60th percentile: 2.2303841590881346
70th percentile: 2.319777584075928
80th percentile: 2.461378479003906
90th percentile: 2.6551868438720705
95th percentile: 2.7520910263061524
99th percentile: 2.829614372253418
mean time: 2.2472586631774902
Pipeline stage StressChecker completed in 14.00s
Running pipeline stage DaemonicModelEvalScorer
Pipeline stage DaemonicModelEvalScorer completed in 0.12s
Running M-Eval for topic stay_in_character
Running pipeline stage DaemonicSafetyScorer
M-Eval Dataset for topic stay_in_character is loaded
Pipeline stage DaemonicSafetyScorer completed in 0.27s
%s, retrying in %s seconds...
%s, retrying in %s seconds...
mistralai-mixtral-8x7b-instruct-v0-1_v3 status is now inactive due to auto deactivation removed underperforming models
admin requested tearing down of mistralai-mixtral-8x7b-instruct-v0-1_v3
Running pipeline stage ISVCDeleter
Checking if service mistralai-mixtral-8x7b-instruct-v0-1-v3 is running
Tearing down inference service mistralai-mixtral-8x7b-instruct-v0-1-v3
Toredown service mistralai-mixtral-8x7b-instruct-v0-1-v3
Pipeline stage ISVCDeleter completed in 3.31s
Running pipeline stage MKMLModelDeleter
Cleaning model data from S3
Cleaning model data from model cache
Deleting key mistralai-mixtral-8x7b-instruct-v0-1-v3/config.json from bucket guanaco-mkml-models
Deleting key mistralai-mixtral-8x7b-instruct-v0-1-v3/flywheel_model.0.safetensors from bucket guanaco-mkml-models
Deleting key mistralai-mixtral-8x7b-instruct-v0-1-v3/flywheel_model.1.safetensors from bucket guanaco-mkml-models
Deleting key mistralai-mixtral-8x7b-instruct-v0-1-v3/flywheel_model.2.safetensors from bucket guanaco-mkml-models
Deleting key mistralai-mixtral-8x7b-instruct-v0-1-v3/flywheel_model.3.safetensors from bucket guanaco-mkml-models
Deleting key mistralai-mixtral-8x7b-instruct-v0-1-v3/special_tokens_map.json from bucket guanaco-mkml-models
Deleting key mistralai-mixtral-8x7b-instruct-v0-1-v3/tokenizer.json from bucket guanaco-mkml-models
Deleting key mistralai-mixtral-8x7b-instruct-v0-1-v3/tokenizer.model from bucket guanaco-mkml-models
Deleting key mistralai-mixtral-8x7b-instruct-v0-1-v3/tokenizer_config.json from bucket guanaco-mkml-models
Cleaning model data from model cache
Deleting key mistralai-mixtral-8x7b-instruct-v0-1-v3_reward/config.json from bucket guanaco-reward-models
Deleting key mistralai-mixtral-8x7b-instruct-v0-1-v3_reward/merges.txt from bucket guanaco-reward-models
Deleting key mistralai-mixtral-8x7b-instruct-v0-1-v3_reward/reward.tensors from bucket guanaco-reward-models
Deleting key mistralai-mixtral-8x7b-instruct-v0-1-v3_reward/special_tokens_map.json from bucket guanaco-reward-models
Deleting key mistralai-mixtral-8x7b-instruct-v0-1-v3_reward/tokenizer.json from bucket guanaco-reward-models
Deleting key mistralai-mixtral-8x7b-instruct-v0-1-v3_reward/tokenizer_config.json from bucket guanaco-reward-models
Deleting key mistralai-mixtral-8x7b-instruct-v0-1-v3_reward/vocab.json from bucket guanaco-reward-models
Pipeline stage MKMLModelDeleter completed in 6.33s
mistralai-mixtral-8x7b-instruct-v0-1_v3 status is now torndown due to DeploymentManager action

Usage Metrics

Latency Metrics